class_docstr: The following is a list of string that can be specified to ``use_up_to`` option in ``__call__`` method;
  
  * ``'detection'`` (default): The output from the last convolution (detection layer) after post-processing.
  * ``'convdetect'``: The output of last convolution without post-processing.
  * ``'lastconv'``: Network till the convolution layer+relu which comes before detection convolution layer.
  
  References:
      * `Joseph Redmon et al., YOLO9000: Better, Faster, Stronger.
        <https://arxiv.org/abs/1612.08242>`_
code: def __init__(self, dataset="voc"):
      # Check validity of num_layers
      assert dataset in [
          "voc",
          "coco",
      ], 'dataset must be chosen from ["voc", "coco"].'
      # Load nnp
      self._dataset_name = dataset
      if self._dataset_name == "voc":
          self._load_nnp("yolov2-voc.nnp", "yolov2-voc.nnp")
      elif self._dataset_name == "coco":
          self._load_nnp("yolov2-coco.nnp", "yolov2-coco.nnp")
  
file_path: nnabla/python/src/nnabla/models/object_detection/yolov2.py
imports: from __future__ import absolute_import
  import nnabla
  from nnabla.utils.nnp_graph import NnpNetworkPass
  import numpy
  from .base import ObjectDetection
label_desc: Use image node_id 1 to create a new YoloV2 object from inherited base classes: ObjectDetection with example: obj = YoloV2(dataset)